This project provides a Graph Database solution designed to combat malnutrition in the elderly. By leveraging Neo4j and Cypher, the system integrates fragmented healthcare data into a unified Knowledge Graph.
The core objective is to bridge the communication gap between General Practitioners (GPs), Nurses, and Dietitians, ensuring that every resident receives a personalized and continuously monitored nutritional care plan.
The system is modeled around a multi-disciplinary care environment, ensuring data integrity and traceability across various medical roles:
- Entities (Nodes):
Resident,General Practitioner (GP),Nurse,Dietitian,CarePlan,HealthRecord. - Relationship Logic:
(Nurse)-[:REPORTS_TO]->(GP): Establishes the clinical hierarchy for medical escalation.(Resident)-[:HAS_CARE_PLAN]->(CarePlan): Directly links patients to specific dietary interventions.(Dietitian)-[:ASSESSES]->(Resident): Captures specialized nutritional evaluations.
The project utilizes optimized Cypher queries to manage complex healthcare scenarios. Below is a key logic example for resource validation:
This query identifies "At Risk" residents and verifies if they have both an assigned Dietitian and an active Care Plan, ensuring no resident is left without professional oversight.
MATCH (r:Resident {status: 'At Risk'})-[:HAS_CARE_PLAN]->(p:CarePlan)
OPTIONAL MATCH (p)<-[:RESPONSIBLE_FOR]-(d:Dietitian)
RETURN r.name AS Resident, p.type AS PlanType, d.name AS AssignedDietitian
## 👤 Author & Credits
- **Database Modeling & UX & System Design**: Yanhui Ma
- **Academic Context**: Developed for the *Information Analysis and Content Management* (ISIT906) course.